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Artificial Intelligence in Teleradiology: A Rapid Review of Educational and Professional Contributions

Artificial Intelligence in Teleradiology: A Rapid Review of Educational and Professional Contributions

Manuel Duarte Lobo
Copyright: © 2023 |Pages: 25
ISBN13: 9781668471647|ISBN10: 1668471647|EISBN13: 9781668471654
DOI: 10.4018/978-1-6684-7164-7.ch004
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MLA

Lobo, Manuel Duarte. "Artificial Intelligence in Teleradiology: A Rapid Review of Educational and Professional Contributions." Handbook of Research on Instructional Technologies in Health Education and Allied Disciplines, edited by Manuel B. Garcia, et al., IGI Global, 2023, pp. 80-104. https://doi.org/10.4018/978-1-6684-7164-7.ch004

APA

Lobo, M. D. (2023). Artificial Intelligence in Teleradiology: A Rapid Review of Educational and Professional Contributions. In M. Garcia, M. Lopez Cabrera, & R. de Almeida (Eds.), Handbook of Research on Instructional Technologies in Health Education and Allied Disciplines (pp. 80-104). IGI Global. https://doi.org/10.4018/978-1-6684-7164-7.ch004

Chicago

Lobo, Manuel Duarte. "Artificial Intelligence in Teleradiology: A Rapid Review of Educational and Professional Contributions." In Handbook of Research on Instructional Technologies in Health Education and Allied Disciplines, edited by Manuel B. Garcia, Mildred Vanessa Lopez Cabrera, and Rui Pedro Pereira de Almeida, 80-104. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-6684-7164-7.ch004

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Abstract

In recent years, artificial intelligence (AI) has been progressively merging into the daily practice of many healthcare professionals. Radiology is a branch of medicine that can benefit from these new technological advancements, as it is a data-rich medical specialty and is well-placed to embrace AI. Specifically, radiologists are in a distinctive position to support the AI revolution because of their direct access to a significant amount of data. In turn, these AI tools can improve pathology detection by radiologists, thereby resulting in better, more accurate, and sooner diagnostics. The chapter aims to provide some new insights into AI concepts, tools, and their application in medical imaging. Several technologies are becoming more available in all imaging modalities, as the COVID-19 pandemic forced a rapid transition to a new era of digital health. In conclusion, the next generation of AI-based diagnostic imaging systems will surely have a serious impact on daily educational and healthcare institutions for the next generation.

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